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embedding parts

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Embedding parts in shape grammars using a parallel particle swarm optimization method on graphics processing units
Hacer Yalim Keles
Journal:

AI EDAM / Volume 32 / Issue 3 / August 2018

Published online by Cambridge University Press:

02 July 2018, pp. 256-268
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Embedding emergent parts in shape grammars is computationally challenging. The first challenge is the representation of shapes, which needs to enable reinterpretation of parts regardless of the creation history of the shapes. The second challenge is the relevant part searching algorithm that provides an extensive exploration of the design space–time efficiently. In this work, we propose a novel method to solve both problems; we treat shapes as they are and use a parallel particle swarm optimization-based algorithm to compute emergent parts. The execution time of the proposed method is improved substantially by dividing the search space into small parts and carrying out searches in each part concurrently using a graphics processing unit. The experiments show that the proposed implementation detects emergent parts accurately and time efficiently.